code: def get_differencers(
      data: pd.DataFrame, target: str, group_cols: List
  ):
      differencers = {}
      grouped = (
          data.groupby(by=group_cols)
          if group_cols
          else data.groupby(lambda x: True)
      )
      for group, subset in grouped:
          differencer = Differencer()
          differencer.fit(subset[target].values)
          differencers[group] = differencer
      return differencers
  
file_path: lightwood/lightwood/data/timeseries_analyzer.py
imports: from typing import Dict, Tuple, List
  import numpy
  import pandas
  from type_infer.dtype import dtype
  from lightwood.api.types import TimeseriesSettings
  from lightwood.helpers.ts import get_ts_groups, get_delta, Differencer
  from lightwood.encoder.time_series.helpers.common import generate_target_group_normalizers
label_desc: Use image node_id 4 for calling a global function with example usage: get_differencers(data, target, group_cols) and returns: differencers